Computational complexity and proof systems are fundamental areas in theoretical computer science that explore the limits of what can be computed and how efficiently problems can be solved. Recent ...

Artificial intelligence (AI) is increasingly transforming computational mechanics, yet many AI-driven models remain limited by poor interpretability, weak generalization, and insufficient physical ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I examine the crucial debate about whether ...

Multimodal large language models have shown powerful abilities to understand and reason across text and images, but their ...

In the ever-evolving landscape of artificial intelligence, there is a growing interest in leveraging insights from neuroscience to create more ...

Biomedical Artificial Intelligence and Computational Modeling are new emerging areas in biomedical engineering. These areas cover: Data analysis and interpretation: developing and applying algorithms ...

Time. We use it to organize our lives, measure our experiences, and impose structure on reality. But what if time, as we conventionally understand it, doesn’t actually exist? What if, instead of being ...

Four faculty from various disciplines have collaborated to teach a groundbreaking class: a deep dive into the world of artificial intelligence (AI) and the role that ethics plays as this emerging ...

Published in Acta Mechanica Sinica, this forward-looking study argues that embedding physical laws into AI models is ...

Taken together, these signals suggest one thing: we may be closer to AGI—and to systems capable of passing the Turing ...

Computational complexity and proof systems constitute a cornerstone of theoretical computer science, addressing both the inherent difficulty of algorithmic problems and the efficiency of formal ...